July 17, 2008
Barringer Reliability Tip
From Which Reliability Tool should I use? By H. Paul Barringer
Reliability tools exist by the dozens: what are the tools, why use the tools, when should I use the tools, and where should I use the tools?
Each week we will explain a reliability tool. The details about these tools will be brief as books are written about each item. Think of the presentations below as hors d’oeuvres (a little snack food or starters)—not the main course.
Availability-
What: A tool for measuring the % of time an item or system is in a state of readiness where it is operable and can be committed to use when call upon. Availability ceases because of a downing event which causes the item/system to become unavailable to initiate a mission when called upon. In the simplest view the metric is availability = uptime/(uptime + downtime).
Why: The measure is important for knowing the commitment of time for performing the mission and it usually only involves the use of arithmetic.
When: Often the measurement tool is based on past experiences and the complement of the measurement tool addresses unavailability to perform the task.
Where: In design of a system it is a calculated value and in operation of a system it is a performance index that is often easy to use and provides and index that is understandable to the average person. Today there is a great tendency to “Enronize” availability metrics by using uptime metrics that presents data in the best light (an issue of data integrity) to maximize managerial bonuses by excusing (deducting) downtime from the calculations to put lipstick on the pig. Use the KISS principle. Think of availability in terms of the investor’s typical year of 8760 hours. The no-excuse annual metric in hours is availability = uptime/8760. Suddenly you’ll find a metric of great interest to investors that can be bench marked as a financial issue, and thus motivate the management team to solve real issues of importance to the business. Please note, you can have high availability but many failures and thus low reliability as availability ≠ reliability. Likewise, you can have high availability but little output so team the metric with effectiveness to get the complete story.
